Prior theory suggests that time variation in the degree to which leverage constraints bind affects the pricing kernel. We propose a measure for this leverage constraint tightness by inverting the argument that constrained investors tilt their portfolios to riskier assets. We show that the average market beta of actively managed mutual funds—intermediaries facing leverage restrictions—captures their desire for leverage and thus the tightness of constraints. Consistent with theory, it strongly predicts returns of the betting-against-beta portfolio, and is a priced risk factor in the cross-section of mutual funds and stocks. Funds with low exposure to the factor outperform high-exposure funds by 5% annually, and for stocks this difference reaches 7%. Our results show that the tightness of leverage constraints has important implications for asset prices.

We show that time variation in macroeconomic uncertainty affects asset prices. Consumption volatility is a negatively priced source of risk for a wide variety of test portfolios. At the firm level, exposure to consumption volatility risk predicts future returns, generating a spread across quintile portfolios in excess of 7% annually. This premium is explained by cross‐sectional differences in the sensitivity of dividend volatility to consumption volatility. Stocks with volatile cash flows in uncertain aggregate times require higher expected returns.

Levered noise occurs when no-arbitrage replication hedges fundamentals but amplifies price errors. Motivated by our theory, we use widely-available end-of-day OptionMetrics data to improve accuracy of synthetic dividend strip prices and provide longer samples than prior studies. Term structure point estimates are approximately flat in simple returns (88 bp/month vs. 87 bp/month for short-term dividends vs. index), and upward-sloping in measurement-error-robust logarithmic returns (43 bp/month vs. 77 bp/month). These results from prominent index options show the importance of diagnosing noise in no-arbitrage prices. Prior conclusions of an average downward slope in the equity term structure are not robust.

Unconditional alphas are biased when conditional beta covaries with the market risk premium (market timing) or volatility (volatility timing). We demonstrate an additional bias (overconditioning) that can occur any time an empiricist estimates risk using information, such as a realized beta, that is not available to investors ex ante. Calibrating to U.S. equity returns, volatility timing and overconditioning can plausibly impact alphas more than market timing, which has been the focus of prior literature. To correct market- and volatility-timing biases without overconditioning, we show that incorporating realized betas into instrumental variables estimators is effective. Empirically, instrumentation reduces momentum alphas by 20–40%. Overconditioned alphas overstate performance by up to 2.5 times. We explain the sources of both the volatility-timing and overconditioning biases in momentum portfolios.

We characterize linkages between average returns calculated at different horizons. Theoretically, when stocks incorporate information slowly, average short-horizon returns are downward biased. Buy-and-hold strategies can amplify the effect. In contrast, existing theories analyze price noises that are independent of fundamentals, and buy-and-hold portfolio returns are unaffected. We document horizon effects as large as 10% annualized in daily and monthly style portfolios and international indices. Slow reaction to market information, identified by gradually declining lagged betas, is an important cause. These findings have natural consequences for performance evaluation.

We characterize linkages between average returns calculated at different horizons. Theoretically, when stocks incorporate information slowly, average short-horizon returns are downward biased. Buy-and-hold strategies can amplify the effect. In contrast, existing theories analyze price noises that are independent of fundamentals, and buy-and-hold portfolio returns are unaffected. We document horizon effects as large as 10% annualized in daily and monthly style portfolios and international indices. Slow reaction to market information, identified by gradually declining lagged betas, is an important cause. These findings have natural consequences for performance evaluation.

Firms with high levels of organization capital (OK), a firm-specific production factor provided by key employees, are known to be risky and earn high stock returns. We argue that fragility of OK (i.e., its sensitivity to potential disruptions) is an independently important dimension of this risk. We proxy for fragility by the size of the top management team and show that firms with small teams outperform firms with big teams by 5% annually. The return spread increases in the level of OK and correlates with the outside options of top executives. Further supporting our interpretation, shocks to team composition from unexpected deaths of chief executive officers cause larger value losses in smaller teams.

We develop a new method to estimate Tobin's Qs of conglomerate divisions without relying on standalone firms. Divisional Qs differ considerably from those of standalone firms across industries, over time, and in their sensitivity to economic shocks. The differences are explained by intraconglomerate covariance structures and access to internal capital markets that mitigate external financing frictions. Consequently, the Qs capture variation in the allocation of assets in the economy: within firms through internal capital markets and across focused and diversified firms through diversifying acquisitions. Overall, our method provides opportunities to study the economic mechanisms that explain corporate diversification.

In an effort to increase transparency, the chair of the Federal Reserve now holds a press conference (PC) following some, but not all, Federal Open Market Committee (FOMC) announcements. Evidence from financial markets shows that investors lower their expectations of important decisions on days without PCs and that these announcements convey less price-relevant information. Correspondingly, we show that investors pay more attention to upcoming announcements with PCs. This coordination of attention can reduce welfare in models of the social value of public information. Consistent with theories of investor attention, the market risk premium is larger on days with PCs.

We show that unpriced cash flow shocks contain information about future priced risk. A positive idiosyncratic shock decreases the sensitivity of firm value to priced risk factors and simultaneously increases firm size and idiosyncratic risk. A simple model can therefore explain book‐to‐market and size anomalies, as well as the negative relation between idiosyncratic volatility and stock returns. Empirically, we find that anomalies are more pronounced for firms with high idiosyncratic cash flow volatility. More generally, our results imply that any economic variable correlated with the history of idiosyncratic shocks can help to explain expected stock returns.